When I explain to people that supply chain 3.0 is real, in general, I get three type of responses. Most of the McKinsey (or their clone) trained strategists ask me to show data to back up this assertion. On the other hand, more intuitive executives (mainly from sales and marketing background, as I observe) ask me to explain the benefits of supply chain 3.0. Finally, the third group – those who I call the transformational leaders ask a simple question – how can we use the power of supply chain 3.0 in effecting beneficial business transformations. In this blog I will address the first question. I will leave for later blogs the remaining two questions and other arising questions such as: how does supply chain 3.0 differ from the previous versions of supply chains, and, why it was even necessary to ‘invent’ supply chains in the first place. It is an important question – “where is the data to clearly demonstrate that Supply Chain 3.0 is real?” The data driven crowd has a legitimate concern lest a couple of isolated examples be seen as heralding a trend. Having trained at a similar top-tier consulting house during my formative years in consulting, I fully understand and endorse their questions. Why? Because all of us have seen people taking isolated instances and exceptions and making them so big in their own and others’ perceptions that these appear to be the predominant trends. Nay-sayers will take a few stray instances of setbacks, blow them out proportion to support their naysaying. On the other hand, almost all investment projects also have their share of overly optimistic projectionists. In the end, only data reveals the overall picture and clarifies the confusion. For this reason, when I wrote the book “The 5-STAR Business Network“, our team did a 6 year longitudinal study of the top 1200 corporations around the world. There were other reasons why this study was conducted – which are given in Chapter 14 of the book. The full research methodology and the resulting ranking of the companies is also given in the book, but for our purpose here it is interesting to note that 62 companies out of the entire starting sample of the top 1200 companies in the world scored 20 points out of 25, which is our cut-off for the Supply Chain 3.0. Also, interesting to note is that Apple – the darling of supply chain crowd – is only ranked #60 in the rankings. And, due to its low margins, Amazon – just missed the cut. So who are the top 35 companies in these rankings? You can see them in figure 1 below. For the time being ignore the 5 colour coding, as well as funny three-letter acronyms (TLAs) in the figure. I am absolutely sure, that this figure is unlike any other figure you might have seen before. Firstly, the companies themselves come from around the globe – Novo Nordisk is from Denmark while Fanuc is from Japan and Falabella is from Chile. That was to be expected – if you make your research wide and deep enough you will find good companies everywhere. No country, or continent has monopoly on excellence. So much for all the hype about the Asian century. Sure, development in Asia is creating unprecedented opportunities – but good companies around the globe are using that trend to their benefit. You do not need to be an Asian company to be excellent, but neither are all non-Asian companies uniformly good.
Secondly, because this ranking is based on study conducted over 5 years (not at a single point in time) the standards of excellence are much higher. Also, this is a global study hence the sample base was much wider. For this reason many of the usual suspects that you might have seen elsewhere in magic circles etc. are missing. Another reason, the usual suspects might be missing is because we looked far beyond tactical operations into the strategic contribution of supply chains to corporate results. For example, rarely has anyone tried to gauge the impact of supply chain collaboration on innovation, new product development, pipeline of products, product phasing etc. But in our research, we took these into account. For details of the research methodology, caveats, cautions and warnings about not applying these results for investment decision making please read Chapter 14 of the book “The 5-STAR Business Network“. This is critical because I do not want you to take the results out of context and make decision based on flawed assumptions. Time has come to talk about the 5 funny acronyms in the figure. This is because we want to see how these are linked to the strategic contribution of supply chain management to overall corporate results. So, what do these TLAs stand for? Figure 2 below shows the details:
Each of these names are quite self-explanatory and most people reading this blog will not need too much explanation. I will only briefly outline them here, because detailed explanation and examples mean that I will be recreating the book “The 5-STAR Business Network” or a version of it in this blog. One more important conclusion needs to be drawn from the data presented in Figure 1. You will notice that rarely is there a company which ranks high on each of the five key cornerstones of supply chain 3.0. Yet, all the 62 excellent companies that meet our criteria for supply chain 3.0 excel in at least three of the five key cornerstones. That shows you do not have to perfect to arrive at supply chain 3.0 – you only need spikes of excellence in at least three of the five key areas. In the next two entries, I will write about each of these five pillars in more details.
In the last entry, I have given you a brief outline of the five pillars supporting Supply Chain 3.0. Let’s now talk about the first two. The first is termed Fire-Aim-Ready (FAR) Innovation. Clearly, it is about creating new (better) products and services, as well as new (better) ways of configuring and delivering existing products and services. Many in supply chain – especially those from logistics or procurement – wonder what do they have to do with innovation. This mindset of not-invented-here survives from the days of materials handling (pre-supply chain days, or Supply Chain 0.0 days) in many quarters and gives supply chain a bad name when it manifests itself. But let me ask them this – How did Apple create and launch products in nearly half the time it took its rivals while keeping utmost secrecy about the product features? The answer will give a clue to how important it is to choose the right suppliers and create the right supply chain arrangements that elevate the supply chain to lofty heights. Apple is only the most visible example, there are many more in the book 5-Star Business Network. Looking at the entire dataset, here is how the companies stack up on Fire-Aim-Ready Innovation.
You might ask why there are only 650 companies in the dataset when we started with 1200 companies. The reason is that over the period of the study (five-years) many of the top 1200 companies were acquired, or merged with other companies to change names. Also, many others dropped out of the top 1200 companies and were no longer of interest to us. In the end only 932 companies survived (we have ignored banks, insurance and utility companies) over 5 years in their original form to be useful for a longitudinal external study of this nature. Some companies (mainly in Banking, Finance, Insurance, Utilities and other such sectors) were not of interest to us because of their opaque supply chains and highly regulated operations. At this point it is useful to also state that every company in the dataset was given a ranking based on the quintile it fell into on each of the five measures. That is why maximum possible points were 25. Full methodology is available in the source document, but the reason was that external data is rarely reliable enough to rank more accurately than that. The second measure of interest to us is the $eed-to-$tore Efficiency. This, is of course, the darling of the supply chain crowd especially those coming out of logistics background. Right product, in right place, in right quantity, at right time (there are many other Rs which people add on, but we will stay simple here) – is the catch phrase. The aim is to churn the cash faster so that more of it sticks around for longer. Consider Figure 2 below which shows profits margins on sales for 2012 for 932 companies ranked in a descending order. The names of the companies are not shown on the figure, and all we are interested in is to divide this universe of companies into five sub-universes ranked by profit margins. The highest ranked 20% of the companies get a score of 5 on $eed-to-$tore efficiency because indeed profit margins are derived from efficiencies.
Even if in some cases, such as Amazon’s margin of 1%, where the profit margins are very low placing them lower on $eed-to-$tore efficiency measure than would be warranted from other internal variables, this deficiency will be made up in other measures such as Market Value to Profits ratio (for example in Amazon’s case it is 125 compared to the market average of 14.9). Let us see how that happens. Consider Figure 3 which shows similar detail for Market Value to Profits Ratio for the same 932 companies in a descending order. Obviously the order has changes this time and Amazon is not middle of the pack in this figure; rather it is one of the top performers. We use this measure as a proxy for Fire-Aim-Ready innovation – a variable which is notoriously very hard to define and measure. However, as a proxy, market price has built into it the expectations of future earnings coming from investment into useful and profitable innovation.
Again the proxy may not be perfect. For example Amazon is ranked one of the highest on this measure though there are other companies which might be far more innovative. However, when measured over a database of more than 1000 companies, and using rankings, rather than absolute numbers for these variables, it is possible to discernable spread of data on each of the variables of interest. Top 20% of the companies for each variable were given a score of 5, next 20% were given a score of 4 and so on, with the bottom 20% of the spread given a score of 1. In part 3 of this blog series, I will go over the remaining three pillars underpinning Supply Chain 3.0.
In the last entry, I have talked about the first two pillars underpinning Supply Chain 3.0. So, what are the other three key cornerstones? Transaction Optimisation Profitability (TOP) measures the ability to simultaneously minimize the costs, and maximize the revenues on each transaction that a company enters into. Consider this – there are companies today that change their pricing dynamically more than 10 million times a month. Why? To able to maximize their revenue based on pricing power they gain out of big data analytics. On the other hand these, and other, companies are constantly looking at ways to shave off fractions of pennies from each of their cost creators. There is a full discussion (chapter 10) of this in the book “The 5-STAR Business Network“ and, if time allows, I might even write a whole book on this topic alone at some time in future. This is after all the hallmark of supply chain 3.0. Advanced Product Phasing (APP) measures the ability of a company to create a pipeline of products that lead it to sustain its market leadership. How many one-hit wonders such as blackberry have you seen? Is Apple, after Steve Jobs, losing its Advanced Product Phasing capability? How can a company balance its drive to milk the current products with its drive to create new products? These are some of the interesting questions that you can explore in more detail once you start thinking in the realms of Advanced Product Phasing (APP). Suffice it to say here that it is one of the key cornerstones of supply chain 3.0. Finally, Results-focused, Modularised Outsourcing (ROM) is so important to supply chain 3.0 that I have already written a follow-up book to talk about this concept. If you read nothing else on this topic, just the foreword by an illustrious strategist and CEO (Philippe Etienne, Managing Director & CEO, Innovia Security Pty Ltd) is worth reading. Here is an excerpt:
Today, when I mentor C-Level executives on how to make the jump to the role of CEO, many struggle to move their thinking from functional excellence to cross-functional leadership. In many people’s minds, even the characterization of a corporate leader seems to be shrouded in mystery– ranging from a motivational speaker to a whip wielding slave-driver. One thing I have noticed all good corporate leaders have in common is their ability to pick and extract the power from uncommon teams – teams of internal experts and external service providers who can aggregate, work well together under pressure, and create the magic called success. That is where it becomes critical to outsource well. No doubt, today every company outsources at least some part of its activities. With outsourcing being so ubiquitous now, and of such strategic importance that some of the best known businessmen on earth spend a significant amount of their time getting it right – it is a wonder why many people are not taking it just as seriously as these business stalwarts are.
So, what does the data say about how real is supply chain 3.0. We already noted that 62 companies meet the cut-off of 20 points out of 25. Let us now look at the rest of the database and try to answer the question that is on everyone’s mind.As shown in the figure above, only 5% of the companies in our dataset of 1200 global leaders meet the criteria for supply chain 3.0 and another 30% meet the criteria for supply chain 2.0. Rest of the companies (nearly 65% or 780 companies out of 1200) are somewhere between supply chain 0.0 and supply chain 1.0. You can see the list in the appendix of the book “The 5-STAR Business Network“. Just be mindful that no company is uniformly excellent, or sub-par in all its divisions and geographical areas, although the results above show them as such. From our work in various divisions of the same corporation we know that pockets of excellence do exist in many sub-par companies and vice-versa. In fact, one of the biggest sources of supply chain friction is exactly this – the variability (sigma) of supply chain performance between various parts of the same business network. But, that is a topic for another blog. While we have seen from the data above that supply chain 3.0 is real, here and now. In future blog posts we will establish the internal workings of supply chain 3.0 and show the transition points from supply chain 2.0 to supply chain 3.0, from supply chain 1.0 to supply chain 2.0, and further on from supply chain 0.0 to supply chain 1.0. Why was it necessary to ‘invent’ supply chain management in the first place. There already existed the discipline of logistics, materials management, inventory management etc. A company’s position on this spectrum will ultimately dictate its performance. Just as is the case in professional golf or tennis – winners in the game of supply chains or business networks take away bulk of the prize pool.
A false-color satellite photograph of the Amazon River in Brazil. (Photo credit: Wikipedia)
Rivers become amazingly complex in their last few miles. If you have not yet done that try and navigate the Amazon delta from the sea up the river – it is an enlightening experience. As a former ships master, I have had the privilege of navigating up a number of rivers – Ganges, Amazon, St Lawrence, Houston, Delaware, Hudson, Nile, Mississippi, and many others. The complexity of the naturally evolved network of the rivers’ last miles must be seen to be believed. You can get lost for your entire life in the intricate network if you do not retain tight control over your perspective. Today, GPS would be a big help but even then you will need a good map and good navigation skills.
The last mile of every network is almost always the most intricate, complex and difficult to navigate. Think of the human body. The 60,000 miles of blood vessels move blood from the heart to various organs and disperse into smaller veins as they go. To get to our fingertips, blood travels in the smallest blood vessels, capillaries, which are less than 1mm long each. So you can imagine how sophisticated the network is and utmost caution is needed at all times. The same applies to businesses. If you get it right – you will win. Amazon is in news for its attempts to set up the last mile services. This will put them in competition with FedEx and UPS in the territory they have owned for decades. Their core competence is delivery to the last miles. Will Amazon be able to outcompete them? In Amazon’s arsenal is predictive shipping. At the beginning of this year, Amazon has received a patent for its “anticipatory shipping” technique. Possessing intimate knowledge of their customers, sometimes even more than the customers themselves, Amazon can control the entire end-to-end supply chain, they can create shops, they can change the entire e-commerce sphere. The odds seem to be in their favour. They can hire and learn from UPS or FedEx. Infrastructure can be bought off the shelf. They also have very high quality self-developed software. But the jury is still out. If they fail – they will lose their shirt. The last mile of every network can bankrupt a company because of the sheer complexity, cost and customisation involved. Surely, you wouldn’t want to be in a situation where there was only $5,000 left in your company’s pocket. Not everyone would be as lucky as the founder of FedEx who gambled that amount and turned it into $32,000, just enough to save the company back in the 1970s. For many others, bankruptcy was inevitable. Webvan filed for bankruptcy in 2001 for being over-optimistic about its “last mile” while the real issue lied in how to get customers to the first mile. Good Amazon waited. Why? Because their strategies build on each other. If Amazon succeeds, it will build a 5-STAR Business Network that will give it a substantial, lasting competitive advantage – over not only retailers, but also courier companies and distributors. At a later stage, once it has figured out its own network, it can outsource what is not considered necessary. What will it outsource? Practically everything except for customer facing interface. Because that gives it immense strength in the 5-STAR Business Network. Its ability to understand customers and make them the right offers. Fulfilment can be modularised and outsourced – but only once Amazon knows the best way to do it themselves.
Following two benefits outlined in the previous entry, in this last entry of the blog series, let us go over the remaining benefits of Supply Chain 3.0.
Recall from the previous blog series that “The second measure of interest to us is in Supply Chain 3.0 is the $eed-to-$tore Efficiency. I mentioned that this is the darling of the supply chain crowd especially those coming out of logistics background. Right product, in right place, in right quantity, at right time (there are many other Rs which people add on, but we will stay simple here) – is the catch phrase. The aim is to churn the cash faster so that more of it sticks around for longer.” In fact, the data from a systematic study carried out by the Aberdeen Group reveals two critical insights. Firstly, the companies with more robust business networks have far superior cash conversion cycle – nearly 6 times better cash conversion cycle. Take a look at Figure 1 below:Secondly, and more importantly, their cash conversion cycle actually improved during the 2 years of testing times leading up to the global financial crisis, while the rest of the industry went backwards. As you can see in Figure 2, 92% of business network masters have improved their cash to cash cycle over the two years leading up to the Global Financial Crisis (GFC) while only 18% of business network laggards have improved it, while for 29% of them it became worse. Is the result shown in figure 2 surprising? Hardly, if you reconsider the story of Nokia vs. Ericsson in the last blog entry. Same catastrophic fire nearly decimated one company while left the other one even stronger to later face onslaught of another supply chain 3.0 hero – that of iPhones.
In economic booms, whether accompanied by economic volatility, or economic stability, supply chain 3.0 allows you to realise higher profits, quickly. In fact the potential of your company’s capabilities are multiplied many times over, perhaps by a factor of as much as 100 or more, by the leverage effect provided by your supply chain 3.0. How? Let us consider an example – the booming commodities industry. In the last 10 years to 2012, no other industry has boomed as much as the commodities industry. Prices of iron ore, copper, coal, gold etc. have gone up exceptionally during this period. Within this industry, iron ore is one of the largest and most capital intensive operations – dominated by three global giants BHP Billiton and Rio Tinto of Australia, and Vale of Brazil. In this scenario, to build a large iron-ore producer and exporter from scratch took Andrew Forrest of Fortescue Metals the full extent of supply chain 3.0. To raise finances, to build mining infrastructure, to build and gain access to the logistics infrastructure and to market the product in the international commodities trade, Fortescue Metals built a capacity in 3 years that many of its much bigger rivals would have taken more than 30 years to build. This was only possible through extensive utilisation of business networks that the company built, nurtured and managed effectively into creating a supply chain 3.0.
Recall my earlier example of companies using supply chain 3.0 to configure more flexible labour force through use of sub-contractors and outsourcing. In volatile times this is essential to smooth out the earnings. Now let us look at a more concrete example, in a highly volatile industry. Global bulk shipping industry is one of the most volatile industries, with the shipping rates falling as much as 94% with a period of 4 weeks, or rising up to 400% with a period of few months. In such a volatile business environment, budgeting and planning can become a nerve-racking exercise for all the companies except those which use their supplier networks to cushion the lean periods with long term contracts and find scarce capacity during the boom periods. We have only seen a few examples of benefits that supply chain 3.0 – a business network of collaborating entities – can create for businesses. I will discuss more examples and as well as how to get there in future blogs.
After delivery drones, Amazon has created yet another news sensation! This time with predictive shipping and patenting it. In this article, Cathy Morrow Robertson describes Amazon’s latest leap:
“Based on previous orders, product searches, wish lists, shopping cart contents and other online customer experiences, Amazon has received a patent for what it calls “anticipatory shipping” – shipping products that it expects customers in a specific area will want to purchase.
Flow charts abound in Amazon’s patent filing that outlines the different ways how this shipping will work. Based on analysis of the vast data Amazon collects on customers and visitors to its website (and maybe via social media websites) it will send items to hubs or maybe even by-pass these hubs all together, without specific addresses on the packages, to regions in which it expects the item(s) to sale. These items may be offered at a special price and, if sold, addresses will then be generated and delivered. The use of barcodes are utilized to monitor the packages and there are proposed processes to handle returns outlined in the patent application. For more specifics, read the patent filing in full here. This new shipping process is what many are describing as a way for Amazon to further cut delivery costs and times- by moving goods closer to the customer ahead of time and then offer same-day or next-day delivery.” This is even more intense than Google’s predictive search function. Here, Amazon presumes to know more about you than you know yourself. Before you even order something, they will ship it in the knowledge that they can make money doing it! How is this possible? Before jumping into any analysis, let’s go back a few centuries to before the industrial revolution. Every piece of clothing, every shoe, in fact almost everything was hand made for the individual buyers that needed it. With the industrial revolution, the cost of production went down by such an amount that it paid to mass produce goods in the hope that someone would buy it later. Most of the goods were sold to buyers who walked in as and when they needed the goods and unsold inventory was disposed of at lower prices. Overall, sellers made huge profits due to increased volumes. Later, methodologies including statistical analysis of buyers’ aggregate demand patterns yielded better inventory optimisation opportunities to lower costs even further in this make-to-stock world. Now, Amazon is moving the goal post one step closer to buyers with this new paradigm of ship-to-stock. This heralds a massive transition from the industrial revolution to the information revolution. As more and more data about customers is collated, verified, parsed and analysed, behavioural patterns emerge allowing Amazon to identify buying triggers and propensity. I do not want to go into a lot of detail of BIG DATA or behavioural pattern scoring through business intelligence algorithms. That they are very effective is illustrated by several case studies in my book “The 5-STAR Business Network“. I write not only about Amazon, but also Target and other retailers, who use these advanced techniques to optimise their profits for each and every transaction. This is called Transaction Optimisation Profitability (TOP) in my above named book, which include differential pricing, bundling, customised offerings, coupons, and other means of sophisticated revenue maximisationThis drive to simultaneously minimize the costs and maximise the revenues on each and every transaction is called Transaction Optimisation Profitability (TOP) in my above named book. Amazon’s reported leap to ship-to-stock may even help it stay on top of the TOP game. In one swoop it will dismantle one of the biggest objections to online shopping – having to wait for the items. At the same time, with its superior knowledge of you, the customer, they can offer just the right price that will entice you to make the purchase once the item is shipped. As a backup for unpurchased items, it will have to negotiate very good shipping rates for returns with the courier companies who are benefiting immensely from the online shopping boom (where are people who predicted the death of courier companies after faxes and emails replaced physical paper?) An even more sophisticated strategy would be to buy or create a chain of specialist stores where a package with your name on will always be waiting for you just in case you want to purchase what you have been browsing online. This will totally change the face of retail from “Stack it high, and sell it low (or, in some cases sell it high)” to “stack it close, sell it fast”. There will be several possible consequences. Not only could this be the final nail in the coffin of traditional retail as we have known it for the last 50 years, but it could also mean that only a few traditional retailers (those who are well advanced with their own big data applications) will be able to survive such a massive business model transformation. I would not like to name those most likely to become the road-kill but it seems likely that Target will give Amazon stiff competition. Moreover, you may find that Amazon is in the market to buy one of the smaller chains with access to the last mile – e.g. 7-11, or another corner store. Alternatively, you may find them starting their own chain similar to Fed-Ex Kinko and the UPS store. If you are working in the private equity arena, then you will notice that such chains as Pack-and-Send will become far more valuable in future. I have tried to keep the technical jargon to minimum in this above blog post, and focused mainly on the business impact. Yet, some of the terminology or concepts may not be fully understandable to some non-technical people. Got something to ask or discuss, please feel free to contact me (I am sure you can find how). Over the next couple of weeks, keep an eye on more blogs on the fate of traditional retail, how Amazon’s trendsetting move will impact industries as diverse as shopping centres and courier companies. On a final note, it also raises interesting questions about patents – because you could argue that allowing patents on predictive shipping is the same as allowing patents on mass production or the industrial revolution!
Troubles in big data are starting to emerge. I have written about these earlier, and warned the clients to first make sure their small data is working as intended before jumping into big data. If you cannot control your small data, your ERP system, your EIS or your cloud then forget about BIG data. All you will have is a big mess instead of a small mess. Despite companies spending hundreds of millions of dollars in their systems renewal efforts, user satisfaction remains stubbornly low. As I say in my book ‘The 5-STAR Business Network’:
Not too many years ago, a very large corporation operating worldwide, made news with the downgrading of their earnings expectations due to supply chain system’s implementation setbacks. The expectation was that the new system would reduce the new production cycle from 1 month to 1 week. Furthermore, it would better match the demand and supply of its products to place the correct products in the right locations and quantities, all at the right time – a very lofty goal. The company spent an enormous amount of money, exceeding US $400 million in order to achieve its aim. However, the software system ‘never worked right’. It caused the factories to crack out too many unpopular products and not enough of the trendier ones in high demand. While making the earning downgrade, the CEO asked the rhetorical question, ‘is this what we get for $400 million?’
The market analysts were not surprised. One respected market analyst [AMR] commented, ‘fiascos like this occur all the time but are usually kept quiet unless they seriously hurt the bottom line.’ Another respected market analyst commented that while the CEO made it sound like it was a surprise for him, if he did not have checkpoints for the projects, he does not have control over his company. A third analyst commented that companies are confused by escalating market hype and too often underestimate the complexity and risks. Another [Forrester Research] commented ‘when the software projects go bad companies are more likely going to scurry up and cover it up because they fear that they are the only ones having trouble. But far from it; our conversation and research reveals this company was not unique or the only one having this kind of trouble‘.
Despite their lofty goals, many of the large information technology deployment projects derail. It takes time for the word to filter out because, in most cases, the executives involved in the process are far too embarrassed to talk about what happened. They do mutter among themselves; after several similar instances the mutterings become more vocal and a trend emerges where a number of people start talking about the shortcomings of the system itself or the implementation process or of the time taken for implementation. Because the cost of this failure is so high – greater than $400 Million in the above case – it is instructive to understand the real root causes of this failure.
All the above problems with small data are only multiplied big time when they apply to big data. However, this blog post is not about these small problems. Most companies survive these small problems by stumbling through them. Now even BIGGER problems are emerging with Big Data. Target was always one of the poster childs of big data. Highlighted in Charles Duhigg’s book and several newspaper articles were its capabilities of predictive behavioural scoring in order to maximise the revenues.
Kashmir Hill, writing in Forbes magazine online in February 2012, cited New York Times in an instance of How Target Figured Out A Teen Girl Was Pregnant Before Her Father Did. 
Target assigns every customer a Guest ID number, tied to their credit card, name, or email address that becomes a bucket that stores a history of everything they’ve bought and any demographic information Target has collected from them or bought from other sources. [They] ran test after test, analyzing the data, and before long some useful patterns emerged. … Take a fictional Target shopper named Jenny Ward, who is 23, lives in Atlanta and in March bought cocoa-butter lotion, a purse large enough to double as a diaper bag, zinc and magnesium supplements and a bright blue rug. There’s, say, an 87 percent chance that she’s pregnant and that her delivery date is sometime in late August.
The anecdote quoted in the article by Kashmir Hill where a father storms angrily into target demanding an apology for encouraging his teenage daughter to get pregnant by mailing her coupons of baby stuff, only to retract the demand later on when he discovers that she was indeed already pregnant, demonstrated the power of predictive business intelligence. This article as well as the New York Times article  by Charles Duhigg and the book it is based on The Power of Habit: Why We Do What We Do in Life and Business also by Charles Duhigg. I quoted this example in my book as well, and cited Target’s ability cautiously. Back of my mind were the concerns about data integrity and security – which have now come true. This holiday season, Target was one of the two large retailers who felt the brunt of the hackers. As per this news report in NBC: Target said Wednesday that the cyber criminals who breached its system used credentials they stole from one of the retailer’s vendors. “The ongoing forensic investigation has indicated that the intruder stole a vendor’s credentials, which were used to access our system,” Target spokeswoman Molly Snyder said in a statement. She declined to elaborate on what type of credentials were taken from the vendor. Meanwhile, the Justice Department is investigating the hacking, Attorney General Eric Holder said Wednesday. While target is not the only one to have suffered such lapses – it is one of the most serious. Reminds me of the joke where a bank robber was asked why did he always rob banks, and he replied because that is where the money is. The news report quoted above shows the magnitude of the theft. Target has said a breach of its networks during the busy holiday shopping period resulted in the theft of about 40 million credit and debit card records and 70 million other records with customer information such as addresses and telephone numbers. Target has not yet specified which vendor was responsible for breach, and whether it was an IT vendor, or a supply chain vendor. Target was not the only one though. Nieman Marcus was another high profile retailer in similar situation, albeit on smaller scale. In fact there were more; in the news report above: Reuters reported Jan. 23 that the FBI has warned U.S. retailers to prepare for more cyber attacks after discovering about 20 hacking cases in the past year that involved the same kind of malicious software used against Target. Final point this episode highlights is the axiom that you will always pay for your vendors sins. I use the example of BP’s oil rig in my book to illustrate that point. Will write on this aspect of the episode in a later blog.
Wires are abuzz with the talk about Satya Nadella – who seems to be the front runner for the job of Microsoft CEO. Many profiles have emerged online – e.g. see the article Satya Nadella: The man who may soon become Microsoft CEO. Google’s Sunder Pichai was also in the race. Microsoft is at a stage of lifecycle where it is transitioning from a traditional corporation into a 5-STAR Business Network in order to compete better with the likes of Google and Apple. Smaller, nimbler competitors such as Contactually, Asana, MailChimp – and countless others – are creating easy to use web-based applications and deriving far higher per user revenues than Microsoft manages to achieve. In a few more years both its cash cows will be fully milked, and no new ones are in sight! So what kind of person is needed at the helm at Microsoft at this very moment? What does it take to transform a business from a losing traditional business to a winning 5-STAR Business Network. Ability to integrate internal fiefdoms and build closely linked external networks ranks topmost. Most people in a company climb up the departmental ladder with a tunnel vision – to reach right up to the top of the pyramid. For example see a typical climb for a CFO in a company who might start in budgeting or auditing arm of the finance department and slowly rise up to the rank of a CFO. Similar ladders exist for Chiefs of marketing, sales, IT, Operations, HR or even product departments.
However, the role of the CEO is very different. Instead of the tunnel vision acuity, you need a peripheral vision acuity.
In order to weave all these fiefdoms together into a cohesive organisation. For example, my experience from shipboard command shows that most captains have to rely a lot on the chief engineer and hence seemed to favour chief engineers over chief officers. After all they had been chief officers themselves and could do the role themselves, if they ever had to. But, despite all their engineering knowledge, most captains could never replicate the knowledge base of a chief engineer. That is why those captains who get the best co-operation from the chief engineers, are generally the most successful. A modern organisation is far more complex than the shipboard company. Reporting to a CEO is a complement of 5-10 people and each of them is a potential candidate for the role. Boards prefer executive for the CEO role who can integrate the gaps between the various points of views and get the best performance out of the entire team. While each contender with a real chance is really good at the functional area they come from – whether it is sales, or marketing, or finance or operations – the one that can integrate the entire team and engender a unique shared vision of future that the board can buy into generally get the nod. Inevitably there are gaps between the functional areas. There are also parts of the functional areas that outsourced to third parties – whether in logistics, or IT or marketing. Integrating these external parties into the organisation’s fabric in such a way that they start sharing organisation’s vision as functioning as responsible part of the team is even more difficult. Chief Executives of future will distinguish themselves on this capability – to integrate useful outsiders into the organisation’s fabric, to outsource strategically, to build a business network of mutually dependent entities and to get this network working in unison towards the shared vision.
Besides Google, no other company is as dispersed as Microsoft is today. Ranging from its traditional core offerings to cloud based offering and hardware business – Microsoft needs a person who can integrate the key strengths of each internal group with needed outside expertise in order to come up with offerrings that customers want in significant volume. Microsoft has to stop playing catch up all the time, and start leading from the front. It has to once again create innovative products that customers really want, and will pay gladly for. It has to make its products easy to use – as easy as other cloud-based and mobile applications being sold by its competitors mentioned earlier. All rounder, shy, humble, super nice, collaborative, very technical, deeply engaged, a visionary leader and strong willed – are the words used again and again to describe Satya Nadella, e.g. in the article “Satya Nadella: ‘Mr Nice guy’ could finish first as Microsoft’s next CEO“. The article goes on to state :
That’s how colleagues, friends and a cross section of industry leaders and technology industry watchers describe 45-year-old Nadella. Calling Nadella “among the brightest brains at Microsoft”, Ravi Venkatesan, former chairman of Microsoft India, said “Nadella’s strength lies in building relationships.” …
Nadella fought the hard battles within Microsoft and brought in collaboration within teams,” says Staten James, vice president & principal analyst Forrester research. On what makes Nadella a frontrunner for the CEO job, James adds, “Microsoft’s culture is unique and would take an outsider quite a while to understand and affect change upon. Nadella has already shown that he can drive the kind of change needed for Microsoft.”
That is exactly what is required at Microsoft at the moment. This is the reason why Why Satya Nadella will make a good CEO for Microsoft.
No matter which country you look at today – you see big problems. Emerging problems are currently grappling with massive monetary expansionism triggered by a need to keep currency stability in face of periodic bouts of Quantitative Easings. For example see the article “Rajan Warns of Policy Breakdown as Emerging Markets Fall”. China is grappling with its own issues – including commodities stockpiles and shadow banking – Copper Caps Longest Fall Since 1995 on China Industry Use. Europe continues to be a basket case and US recovery is in doubt – both are well documented in financial press and tweetosphere. It appears that these problems are so massive that there is no way out of them. At national and even regional level – being close to the problems – it appears that there is no resolution is sight. Again, this type of thinking is well document in the financial press and tweetosphere – hence I am not giving any specific links. My key point for this blog is that ‘a problem cannot be solved with the same mindset that created it’. A local, or regional mind-set with never solve the problems that were created with this mind-set. If you look at it from a global perspective the problems do not look as big. Before your biases make you stop reading let me reiterate what I wrote in my book “The 5-STAR Business Network“.
Whatever be the reasons, or the outcomes, of this current global economic scenario, it cannot be denied that eventually only the business will lead recovery in the economy. The failures of command economies in the erstwhile Soviet bloc have demonstrated beyond doubt that statist policies, while good short term band-aid solutions, can rarely lead to true economic prosperity.
Globalisation has been blamed by both the extreme right and extreme left for a host of economic ills facing various nations. Having seen the effects of globalisation at close quarters in more than 100 countries, I cannot disagree more. In my view the results attributed to globalisation are more attributable to other factors such as human malfeasance, institutionalized corruption even in the highest places, laziness, a sense of entitlement to riches without working for them and herd mentality leading to action without thinking and many such factors – all part of basic human nature.
It will be fair to say that one of the most alarming trend has been the continued shifting of the global manufacturing capacity to China. Just like a giant vacuum cleaner, China has sucked in the manufacturing capability from rest of the world at an intense pace over the past 15 years. Isolated stories of reversal of this trend apart, China continues with its policy of government aided industrial expansion far and wide beyond what might be good for Chinese or global economy. Its companies invest even in industries where labour provides little competitive advantage, and China has little capability advantage. This sets up a scene for an international showdown either on economic front or on a military/political front – either of which scenarios will be an unwelcome backlash against globalization leading to a reversal of global economic fortunes.
In the midst of this macro situation, business continue to suffer from intense uncertainty and anxiety. Investment decisions are delayed for months, if not years due to inability to project cash flows and the expected rate of returns for the investors. Waiting for consumer spending to pick up has been futile so far.
The intense volatility in the commodity prices is leading to speculation and perhaps even manipulation in the commodity markets on a global level. At a micro level, this volatility in the prices of raw materials has made it nearly impossible to make and keep budgets, make any price promises, and stabilize customer-supplier relationships in a stable manner professed by traditional supply chain management pundits.
Yes, I have seen the impact of globalisation on ground in more than 100 countries. And yes, it is largely positive. Does Globalisation mean doing away with the rule of law? Obviously, no. I cannot imagine today’s big problems will be solved any other way. That is why Globalisation is inevitable and good. Companies, institutions and governments will do well to prepare for it, and position their constituencies appropriately.